{"id":"https://openalex.org/W2510290113","doi":"https://doi.org/10.1109/icip.2016.7532931","title":"Denoising method selection by comparison-based image quality assessment","display_name":"Denoising method selection by comparison-based image quality assessment","publication_year":2016,"publication_date":"2016-08-17","ids":{"openalex":"https://openalex.org/W2510290113","doi":"https://doi.org/10.1109/icip.2016.7532931","mag":"2510290113"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2016.7532931","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532931","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063500144","display_name":"Haoyi Liang","orcid":"https://orcid.org/0000-0003-4870-4149"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Haoyi Liang","raw_affiliation_strings":["Department of ECE, University of Virginia, Charlottesville, VA, USA"],"affiliations":[{"raw_affiliation_string":"Department of ECE, University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006764308","display_name":"Daniel S. Weller","orcid":"https://orcid.org/0000-0001-9818-7325"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel S. Weller","raw_affiliation_strings":["Department of ECE, University of Virginia, Charlottesville, VA, USA"],"affiliations":[{"raw_affiliation_string":"Department of ECE, University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5063500144"],"corresponding_institution_ids":["https://openalex.org/I51556381"],"apc_list":null,"apc_paid":null,"fwci":0.501,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.72275832,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"20","issue":null,"first_page":"3106","last_page":"3110"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.8014422655105591},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6661977767944336},{"id":"https://openalex.org/keywords/video-denoising","display_name":"Video denoising","score":0.6459031105041504},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6021753549575806},{"id":"https://openalex.org/keywords/non-local-means","display_name":"Non-local means","score":0.5764255523681641},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5703612565994263},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5461259484291077},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5337055325508118},{"id":"https://openalex.org/keywords/image-denoising","display_name":"Image denoising","score":0.5187225937843323},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.49469444155693054},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.48928186297416687},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4779929518699646},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46668538451194763},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38383370637893677},{"id":"https://openalex.org/keywords/video-processing","display_name":"Video processing","score":0.12531572580337524},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.08283689618110657},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06627368927001953}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.8014422655105591},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6661977767944336},{"id":"https://openalex.org/C30814859","wikidata":"https://www.wikidata.org/wiki/Q4119603","display_name":"Video denoising","level":5,"score":0.6459031105041504},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6021753549575806},{"id":"https://openalex.org/C101453961","wikidata":"https://www.wikidata.org/wiki/Q7048948","display_name":"Non-local means","level":4,"score":0.5764255523681641},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5703612565994263},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5461259484291077},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5337055325508118},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.5187225937843323},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.49469444155693054},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48928186297416687},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4779929518699646},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46668538451194763},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38383370637893677},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.12531572580337524},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.08283689618110657},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06627368927001953},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C23431618","wikidata":"https://www.wikidata.org/wiki/Q1404672","display_name":"Multiview Video Coding","level":4,"score":0.0},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2016.7532931","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532931","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1982471090","https://openalex.org/W2008357395","https://openalex.org/W2037243393","https://openalex.org/W2056370875","https://openalex.org/W2103559027","https://openalex.org/W2119999314","https://openalex.org/W2129644086","https://openalex.org/W2133251102","https://openalex.org/W2133665775","https://openalex.org/W2142731874","https://openalex.org/W2147298660","https://openalex.org/W2150427434","https://openalex.org/W2153663612","https://openalex.org/W2171125155","https://openalex.org/W2171349048","https://openalex.org/W2203654268","https://openalex.org/W2207282238","https://openalex.org/W2289843649","https://openalex.org/W2293134380","https://openalex.org/W2295949027","https://openalex.org/W2317084172","https://openalex.org/W2536599074","https://openalex.org/W3098677430","https://openalex.org/W3182211633","https://openalex.org/W6681807782","https://openalex.org/W6699464847","https://openalex.org/W6798736878","https://openalex.org/W6910427128"],"related_works":["https://openalex.org/W233850645","https://openalex.org/W4213271663","https://openalex.org/W2776327255","https://openalex.org/W1538114257","https://openalex.org/W2098237619","https://openalex.org/W4287081060","https://openalex.org/W2035842925","https://openalex.org/W2810018092","https://openalex.org/W2791234060","https://openalex.org/W2360732716"],"abstract_inverted_index":{"Based":[0],"on":[1,7,60],"a":[2,34,42,77,90],"diverse":[3],"range":[4],"of":[5,88],"priors":[6],"natural":[8],"scene":[9],"images":[10],"and":[11],"noise,":[12],"numerous":[13],"denoising":[14,28,43,51,74,91],"algorithms":[15,29,52],"have":[16],"been":[17],"proposed":[18,66,81],"in":[19],"the":[20,65,72,86],"literature.":[21],"The":[22,80],"image":[23,55],"quality":[24,56],"resulting":[25],"from":[26],"different":[27,50],"may":[30],"vary":[31],"significantly":[32],"across":[33],"data":[35,98],"set.":[36],"In":[37],"this":[38],"work,":[39],"we":[40],"propose":[41],"algorithm":[44,75],"selection":[45,68,82],"framework":[46,69],"that":[47,64],"chooses":[48],"among":[49],"using":[53],"comparison-based":[54,67],"assessment.":[57],"Extensive":[58],"experiments":[59],"two":[61],"databases":[62],"show":[63],"consistently":[70],"selects":[71],"SSIM-optimal":[73],"without":[76],"reference":[78],"image.":[79],"method":[83,92],"effectively":[84],"removes":[85],"burden":[87],"selecting":[89],"for":[93],"applications":[94],"involving":[95],"processing":[96],"large":[97],"sets":[99],"automatically.":[100]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}